import torch
in_channels,out_channels=5,10

width,height=100,100
kernel_size=3
batch_size=1

input = torch.randn(batch_size,in_channels,width,height)
conv_layer=torch.nn.Conv2d(in_channels,out_channels,kernel_size=kernel_size)
output = conv_layer(input)

print(input.shape)
print(output.shape)
print(conv_layer.weight.shape)




